Prediction and Context Awareness in Agriculture: A Systematic Mapping

Abstract

The advances in sensorial technology and its use in agriculture have been contributing to the acquisition and analysis of data regarding agricultural production. Studies propose the use of sensors to monitor production or even the use of cameras to obtain crop information, providing data, reminders, and alerts to farmers. Through the obtainment and analysis of these data, context awareness can be used to improve systems, mainly through the prediction techniques applied to agriculture. This article presents a systematic mapping of studies that use prediction and context awareness in agriculture. During the mapping, 10206 articles were initially identified and, after filtering by inclusion and exclusion criteria, 42 articles were selected. The results indicated that 35.7% (15/42) of the studies used one or more prediction techniques and 45.2% (19/42) used image processing through pictures of cameras to obtain information regarding planting. 23 sensors with different functionalities were found, those have been used in the collection of data for context formation in agriculture.

Barriers to and Benefits of the Use of Smart Farming Technologies for Small and Medium Winemakers, Specifically Sensors and Weather Stations: A Pilot Study

“…It is therefore crucial that the ICT options most useful to farmers are identified in order to be able to convey how these targeted agricultural interventions can benefit their operations. This will be crucial in closing the gap between those farmers who willingly use ICT in their daily lives but are more reticent about using SFTs in their professional work Martini et al (2020). present a systematic mapping of studies that use prediction and context awareness in agriculture.…”